Shin, Hyoung Sub;Song, Seok Ho;Lee, Dong Ho;Park, Jong Hwa
Ecology and Resilient Infrastructure
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v.8
no.4
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pp.253-265
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2021
In this study, crop cultivation filed was extracted by using Unmanned Aerial Vehicle (UAV) imagery and deep learning models to overcome the limitations of satellite imagery and to contribute to the technological development of understanding the status of crop cultivation field. The study area was set around Chungbuk Goesan-gun Gammul-myeon Yidam-li and orthogonal images of the area were acquired by using UAV images. In addition, study data for deep learning models was collected by using Farm Map that modified by fieldwork. The Attention U-Net was used as a deep learning model to extract feature of UAV in this study. After the model learning process, the performance evaluation of the model for corn cultivation extraction was performed using non-learning data. We present the model's performance using precision, recall, and F1-score; the metrics show 0.94, 0.96, and 0.92, respectively. This study proved that the method is an effective methodology of extracting corn cultivation field, also presented the potential applicability for other crops.
Proceedings of the Korean Society for Agricultural Machinery Conference
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2000.11b
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pp.300-306
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2000
This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.
Compact Advanced Satellite 500 (CAS500) can be used for various purposes, including vegetation, forestry, and agriculture fields. It is expected that it will be possible to acquire satellite images of various areas quickly. In order to use satellite images acquired through CAS500 in the agricultural field, it is necessary to develop a satellite image-based extraction technique for crop-cultivated areas.In particular, as research in the field of deep learning has become active in recent years, research on developing a deep learning model for extracting crop cultivation areas and generating training data is necessary. This manuscript classified the onion and garlic cultivation areas in Hapcheon-gun using PlanetScope satellite images and farm maps. In particular, for effective model learning, the model performance was analyzed according to the proportion of crop-cultivated areas. For the deep learning model used in the experiment, Fully Convolutional Densely Connected Convolutional Network (FC-DenseNet) was reconstructed to fit the purpose of crop cultivation area classification and utilized. As a result of the experiment, the ratio of crop cultivation areas in the training data affected the performance of the deep learning model.
Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.
Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we developed for estimating garlic growth at field scale model in major cultivation regions. We used the $NDVI_{UAV}$ that reflects the crop conditions, and seven meteorological elements for 3 major cultivation regions from 2015 to 2017. For this study, UAV imagery was taken at Taean, Changnyeong, and Hapcheon regions nine times from early February to late June during the garlic growing season. Four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.), and fresh weight (F.W.) were measured for twenty plants per plot for each field campaign. The multiple linear regression models were suggested by using backward elimination and stepwise selection in the extraction of independent variables. As a result, model of cold type explain 82.1%, 65.9%, 64.5%, and 61.7% of the P.H., F.W., L.N., P.D. with a root mean square error (RMSE) of 7.98 cm, 5.91 g, 1.05, and 3.43 cm. Especially, model of warm type explain 92.9%, 88.6%, 62.8%, 54.6% of the P.H., P.D., L.N., F.W. with a root mean square error (RMSE) of 16.41 cm, 9.08 cm, 1.12, 19.51 g. The spatial distribution map of garlic growth was in strong agreement with the field measurements in terms of field variation and relative numerical values when $NDVI_{UAV}$ was applied to multiple linear regression models. These results will also be useful for determining the UAV multi-spectral imagery necessary to estimate growth parameters of garlic.
The purpose of this study was to confirm the dissolution of arsenic from the stabilized soil around abandoned coal mines by cultivation activities. Experimental soils were collected from the agricultural field around Okdong and Buguk coal mines, and the concentration of arsenic in the soil and the geochemical mobility were confirmed. The average arsenic concentration was 20 mg/kg. The soil with relatively high geochemical mobility of arsenic in the soil was used in the batch and column experiment. The limestone was mixed with soil for soil stabilization, and the mixing ratio was 3% of limestone, based on the soil weight. The phosphoric acid fertilizer (NH4H2PO4) was added to the soil to simulate a cultivation condition according to the Rural Development Administration's rules. Comparative soil without mixing limestone was prepared and used as a control group. The arsenic extraction from soil was increased following the fertilizer mixing amount and it shows a positive relationship. The concentration of phosphate in the supernatant was relatively low under the condition of mixing limestone, which is determined to be result of binding precipitation of phosphate ions and calcium ions dissolved in limestone. Columns were set to mix phosphoric acid fertilizers and limestone corresponding to cultivation and stabilization conditions, and then the column test was conducted. The variations of arsenic extraction from the soil indicated that the stabilization was effectible until 10 P.V.; however, the stabilization effect of limestone decreased with time. Moreover, the geochemical mobility of arsenic has transformed by increasing the mobile fractions in soil compared to initial soil. Therefore, based on the arsenic extraction results, the cultivation activities using phosphoric fertilizer could induce a decrease in the stabilization effect.
Bong, Ki Moon;Kim, Jong Min;Yoo, Jae-Hong;Park, In Chul;Lee, Chul Won;Kim, Pyoung Il
KSBB Journal
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v.31
no.3
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pp.158-164
/
2016
Plant growth promoting (PGP) hormones, which are produced in a small quantity by bacteria, affect in plant growth and development. PGPs play an important role on the crop productivity in agricultural field. In this study, a photosynthetic bacterial strain producing the PGP was isolated from paddy soil. Bacterial isolate was gram negative, rod-shaped and motility positive. From the 16s rRNA gene sequence analysis, the isolate was identified as Rhodobacter capsulatus PS-2. The mass cultivation of R. capsulatus PS-2 was optimized by considering of the carbon, nitrogen and inorganic salt sources. Optimal medium composition was determined as Na-succinate 4.5 g, yeast extract 5 g, $K_2HPO_4$ 1 g, $MgSO_4$ 5 g, per liter. From the result of 500 L fermentation for 2 days using the optimal medium, the viable cells were $8.7{\times}10^9cfu/mL$. R. capsulatus PS-2 strain produced the carotenoid and indole-3-acetic acid (IAA). The carotenoid extraction and quantitative analysis were performed by HCl-assisting method. Total carotenoid contents from R. capsulatus PS-2 culture broth were measured as $7.02{\pm}0.04$ and $6.93{\pm}0.05mg/L$ under photoheterotrophic and chemoheterotrophic conditions, respectively. To measure the productivity of IAA, colorimetric method was employed using Salkowski reagent at optical density 535 nm. The results showed that the highest content of IAA was $197.44{\pm}5.92mg/L$ in the optimal medium supplemented with 0.3% tryptophan.
The field feasibility tests for a phytoextraction process were performed to identify the effect of citric acid as a chelate on the uranium (U) transfer into the plant for the naturally U contaminated soil in Duckpyeongri, Korea. For the feasibility tests, lettuce and Chinese cabbage were cultivated for 49 days on four testing grounds ($1m{\times}1m{\times}0.5m$ in each) in 2016. The citric acid solution was added to two testing grounds (one for lettuce and the other for Chinese cabbage) increasing the U transfer in two crop plants and their results were compared to those without the citric acid solution. When without the citric acid solution, the U concentration of plant after the cultivation was low (< $45{\mu}g/kg$ for leaves and < $450{\mu}g/kg$ for roots). However, with the addition of 50 mM citric acid solution, the U concentration of lettuce leaves and roots increased by 24 times and 1.8 times, and the U concentration of Chinese cabbage leaves and roots increased by 86.7 times and 5.4 times. The absolute accumulated U amount (${\mu}g$) in lettuce and Chinese cabbage also increased by 8.7 times and 50 times, compared to those without citric acid solution. Less than 8% of the U amount of exchangeable/carbonate phases was removed by using the lettuce and Chinese cabbage when the citric acid solution was not applied. However 52% and 66% of the U amount in exchangeable/carbonate phases were removed by the lettuce and the Chinese cabbage when the citric acid solution was added. The effect of the citric acid on the U transfer capability into the plants was quantitatively investigated by the field feasibility test, suggesting that U existing as exchangeable/carbonate phase in soil can be successfully removed by the phytoextraction process using Chinese cabbage with citric acid.
This experiment was carried out to obtain the maximum quantity of essential oil on the basis of harvesting time, cultivation regions & types, and drying methods. We have selected 6 native and introduced herbs viz. $Thymus$$quinquecostatus$, $Agastache$$rugosa$, $Chrysanthemum$$indicum$, $Rosmarinus$$officinalis$, $Chamaemelum$$nobile$, and $Lavandula$$stoechas$. The quantity of essential oil ranged from 0.06% to 3.46% in all six herbs. Native herbs produce 30.5% higher quantity of oil in comparison to introduced herbs. The quantity of essential oil obtained from $Lavandula$$stoechas$ was 3.46%, followed by $Rosmarinus$$officinalis$ 2.89%, while minimum in $Agastache$$rugosa$ 0.60%. Higher quantity of essential oil obtained if they are cultivated under rain shelter culture (PE film) in comparison to open field conditions. Recovery of essential oil is always high if herbs flower in July. Semi-alpine region was found better than the plain region for herbs production. Quantity of oil is high if oil is extracted from fresh herbs followed by freezed herbs, shade dry and hot wind dry herbs. As far as plant part is concern flower produced maximum oil than any other part.
This study was conducted in order to analyze the polyphenol contents and antioxidant activities of hot-water extracts of Aster scaber in the wild field and cultivated field, and through the drying methods for the comparison on the quality characteristics of Aster scaber, according to cultivation and drying methods, and the development of functional materials. The extraction yield was higher in the Aster scaber cultivated field than those of the Aster scaber in the wild field, and high from the dried Aster scaber. The total polyphenol and flavonoid contents of Aster scaber hot-water extracts from the wild field were higher than those in the cultivated field. The total polyphenol contents were high in the extract of blanched and dried Aster scaber, and the flavonoid content was high in the non-treated Aster scaber. The electron donating ability (EDA) values of Aster scaber hot-water extracts were increased along with the increase of extract concentration, while the EDA of the blanched and dried Aster scaber extracts was higher than the other extracts. Furthermore, the SOD-like activity was increased by the extract concentration, and was high in the extract of the non-treated Aster scaber. The nitrite scavenging ability in pH 1.2 was high in the non-treated, blanched, dried, and natural dried Aster scaber. The xanthine oxidase inhibitory activities were increased through the increase of extract concentrations, and higher in the hot-water extract from Aster scaber in the wild field (WRA) than those in the other extracts. The inhibition of tyrosinase and reduction of power were increased by the increased extract concentration, and high in the extracts of blanched and dried Aster scaber. The reduced power was higher in the Aster scaber hot-water extracts of cultivated field, and was higher in the extracts of blanched and dried Aster scaber than those in the extracts dried through the use of other drying methods. Aster scaber has a high content of polyphenol and flavonoid, and antioxidant activities, which were developed as functional materials.
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